/*
 * Copyright 2006-2023 www.anyline.org
 *
 * Licensed under the Apache License, Version 2.0 (the "License");
 * you may not use this file except in compliance with the License.
 * You may obtain a copy of the License at
 *
 *      http://www.apache.org/licenses/LICENSE-2.0
 *
 * Unless required by applicable law or agreed to in writing, software
 * distributed under the License is distributed on an "AS IS" BASIS,
 * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
 * See the License for the specific language governing permissions and
 * limitations under the License.
 */


package org.anyline.util.img;

import java.awt.*;
import java.awt.image.BufferedImage;
import java.awt.image.DataBufferByte;
import java.io.BufferedOutputStream;
import java.io.FileOutputStream;
import java.io.IOException;
import java.io.OutputStream;


public class AnimatedGifEncoder {
 
  protected int width; // image size
 
  protected int height; 
 
  protected Color transparent = null; // transparent color if given
 
  protected int transIndex; // transparent index in color table
 
  protected int repeat = -1; // no repeat
 
  protected int delay = 0; // frame delay (hundredths)
 
  protected boolean started = false; // ready to output frames
 
  protected OutputStream out; 
 
  protected BufferedImage image; // current frame
 
  protected byte[] pixels; // BGR byte array from frame
 
  protected byte[] indexedPixels; // converted frame indexed to palette
 
  protected int colorDepth; // number of bit planes
 
  protected byte[] colorTab; // RGB palette
 
  protected boolean[] usedEntry = new boolean[256]; // active palette entries
 
  protected int palSize = 7; // color table size (bits-1)
 
  protected int dispose = -1; // disposal code (-1 = use default)
 
  protected boolean closeStream = false; // close stream when finished
 
  protected boolean firstFrame = true; 
 
  protected boolean sizeSet = false; // if false, get size from first frame
 
  protected int sample = 10; // default sample interval for quantizer
 
  /** 
   * Sets the delay time between each frame, or changes it for subsequent frames 
   * (applies to last frame added). 
   *  
   * @param ms  ms
   *          int delay time in milliseconds 
   */ 
  public void setDelay(int ms) {
    delay = Math.round(ms / 10.0f); 
  } 
 
  /** 
   * Sets the GIF frame disposal code for the last added frame and any 
   * subsequent frames. Default is 0 if no transparent color has been set, 
   * otherwise 2. 
   *  
   * @param code  code  int disposal code. 
   */ 
  public void setDispose(int code) {
    if (code >= 0) {
      dispose = code; 
    } 
  } 
 
  /** 
   * Sets the number of times the set of GIF frames should be played. Default is 
   * 1; 0 means play indefinitely. Must be invoked before the first image is 
   * added. 
   *  
   * @param iter  iter  int number of iterations. 
   */ 
  public void setRepeat(int iter) {
    if (iter >= 0) {
      repeat = iter; 
    } 
  } 
 
  /** 
   * Sets the transparent color for the last added frame and any subsequent 
   * frames. Since all colors are subject to modification in the quantization 
   * process, the color in the final palette for each frame closest to the given 
   * color becomes the transparent color for that frame. May be set to null to 
   * indicate no transparent color. 
   *  
   * @param c  Color to be treated as transparent on display. 
   */ 
  public void setTransparent(Color c) {
    transparent = c; 
  } 
 
  /** 
   * Adds next GIF frame. The frame is not written immediately, but is actually 
   * deferred until the next frame is received so that timing data can be 
   * inserted. Invoking <code>finish()</code> flushes all frames. If 
   * <code>setSize</code> was not invoked, the size of the first image is used 
   * for all subsequent frames. 
   *  
   * @param im  BufferedImage containing frame to write. 
   * @return true if successful. 
   */ 
  public boolean addFrame(BufferedImage im) {
    if ((im == null) || !started) {
      return false; 
    } 
    boolean ok = true; 
    try {
      if (!sizeSet) {
        // use first frame's size
        setSize(im.getWidth(), im.getHeight()); 
      } 
      image = im; 
      getImagePixels(); // convert to correct format if necessary
      analyzePixels(); // build color table & map pixels
      if (firstFrame) {
        writeLSD(); // logical screen descriptior
        writePalette(); // global color table
        if (repeat >= 0) {
          // use NS app extension to indicate reps
          writeNetscapeExt(); 
        } 
      } 
      writeGraphicCtrlExt(); // write graphic control extension
      writeImageDesc(); // image descriptor
      if (!firstFrame) {
        writePalette(); // local color table
      } 
      writePixels(); // encode and write pixel data
      firstFrame = false; 
    } catch (IOException e) {
      ok = false; 
    } 
 
    return ok; 
  } 
 
  /** 
   * Flushes any pending data and closes output file. If writing to an 
   * OutputStream, the stream is not closed. 
   * @return boolean
   */ 
  public boolean finish() {
    if (!started) 
      return false; 
    boolean ok = true; 
    started = false; 
    try {
      out.write(0x3b); // gif trailer
      out.flush(); 
      if (closeStream) {
        out.close(); 
      } 
    } catch (IOException e) {
      ok = false; 
    } 
 
    // reset for subsequent use
    transIndex = 0; 
    out = null; 
    image = null; 
    pixels = null; 
    indexedPixels = null; 
    colorTab = null; 
    closeStream = false; 
    firstFrame = true; 
 
    return ok; 
  } 
 
  /** 
   * Sets frame rate in frames per second. Equivalent to 
   * <code>setDelay(1000/fps)</code>. 
   *  
   * @param fps  float frame rate (frames per second) 
   */ 
  public void setFrameRate(float fps) {
    if (fps != 0f) {
      delay = Math.round(100f / fps); 
    } 
  } 
 
  /** 
   * Sets quality of color quantization (conversion of images to the maximum 256 
   * colors allowed by the GIF specification). Lower values (minimum = 1) 
   * produce better colors, but slow processing significantly. 10 is the 
   * default, and produces good color mapping at reasonable speeds. Values 
   * greater than 20 do not yield significant improvements in speed. 
   *  
   * @param quality  int greater than 0. 
   */ 
  public void setQuality(int quality) {
    if (quality < 1) 
      quality = 1; 
    sample = quality; 
  } 
 
  /** 
   * Sets the GIF frame size. The default size is the size of the first frame 
   * added if this method is not invoked. 
   *  
   * @param w  int frame width. 
   * @param h  int frame width. 
   */ 
  public void setSize(int w, int h) {
    if (started && !firstFrame) 
      return; 
    width = w; 
    height = h; 
    if (width < 1) 
      width = 320; 
    if (height < 1) 
      height = 240; 
    sizeSet = true; 
  } 
 
  /** 
   * Initiates GIF file creation on the given stream. The stream is not closed 
   * automatically. 
   *  
   * @param os   OutputStream on which GIF images are written. 
   * @return false if initial write failed. 
   */ 
  public boolean start(OutputStream os) {
    if (os == null) 
      return false; 
    boolean ok = true; 
    closeStream = false; 
    out = os; 
    try {
      writeString("GIF89a"); // header
    } catch (IOException e) {
      ok = false; 
    } 
    return started = ok; 
  } 
 
  /** 
   * Initiates writing of a GIF file with the specified name. 
   *  
   * @param file String containing output file name. 
   * @return false if open or initial write failed. 
   */ 
  public boolean start(String file) {
    boolean ok = true; 
    try {
      out = new BufferedOutputStream(new FileOutputStream(file)); 
      ok = start(out); 
      closeStream = true; 
    } catch (IOException e) {
      ok = false; 
    } 
    return started = ok; 
  } 
 
  /** 
   * Analyzes image colors and creates color map. 
   */ 
  protected void analyzePixels() {
    int len = pixels.length; 
    int nPix = len / 3; 
    indexedPixels = new byte[nPix]; 
    NeuQuant nq = new NeuQuant(pixels, len, sample); 
    // initialize quantizer
    colorTab = nq.process(); // create reduced palette
    // convert map from BGR to RGB
    for (int i = 0; i < colorTab.length; i += 3) {
      byte temp = colorTab[i]; 
      colorTab[i] = colorTab[i + 2]; 
      colorTab[i + 2] = temp; 
      usedEntry[i / 3] = false; 
    } 
    // map image pixels to new palette
    int k = 0; 
    for (int i = 0; i < nPix; i++) {
      int index = nq.map(pixels[k++] & 0xff, pixels[k++] & 0xff, pixels[k++] & 0xff); 
      usedEntry[index] = true; 
      indexedPixels[i] = (byte) index; 
    } 
    pixels = null; 
    colorDepth = 8; 
    palSize = 7; 
    // get closest match to transparent color if specified
    if (transparent != null) {
      transIndex = findClosest(transparent); 
    } 
  } 
 
  /** 
   * Returns index of palette color closest to c 
   * @param c color
   * @return int
   */ 
  protected int findClosest(Color c) {
    if (colorTab == null) 
      return -1; 
    int r = c.getRed(); 
    int g = c.getGreen(); 
    int b = c.getBlue(); 
    int minpos = 0; 
    int dmin = 256 * 256 * 256; 
    int len = colorTab.length; 
    for (int i = 0; i < len;) {
      int dr = r - (colorTab[i++] & 0xff); 
      int dg = g - (colorTab[i++] & 0xff); 
      int db = b - (colorTab[i] & 0xff); 
      int d = dr * dr + dg * dg + db * db; 
      int index = i / 3; 
      if (usedEntry[index] && (d < dmin)) {
        dmin = d; 
        minpos = index; 
      } 
      i++; 
    } 
    return minpos; 
  } 
 
  /** 
   * Extracts image pixels into byte array "pixels" 
   */ 
  protected void getImagePixels() {
    int w = image.getWidth(); 
    int h = image.getHeight(); 
    int type = image.getType(); 
    if ((w != width) || (h != height) || (type != BufferedImage.TYPE_3BYTE_BGR)) {
      // create new image with right size/format
      BufferedImage temp = new BufferedImage(width, height, BufferedImage.TYPE_3BYTE_BGR); 
      Graphics2D g = temp.createGraphics(); 
      g.drawImage(image, 0, 0, null); 
      image = temp; 
    } 
    pixels = ((DataBufferByte) image.getRaster().getDataBuffer()).getData(); 
  } 
 
  /** 
   * Writes Graphic Control Extension 
   * @throws IOException IOException
   */ 
  protected void writeGraphicCtrlExt() throws IOException {
    out.write(0x21); // extension introducer
    out.write(0xf9); // GCE label
    out.write(4); // data block size
    int transp, disp; 
    if (transparent == null) {
      transp = 0; 
      disp = 0; // dispose = no action
    } else {
      transp = 1; 
      disp = 2; // force clear if using transparent color
    } 
    if (dispose >= 0) {
      disp = dispose & 7; // user override
    } 
    disp <<= 2; 
 
    // packed fields
    out.write(0 | // 1:3 reserved
        disp | // 4:6 disposal
        0 | // 7 user input - 0 = none
        transp); // 8 transparency flag
 
    writeShort(delay); // delay x 1/100 sec
    out.write(transIndex); // transparent color index
    out.write(0); // block terminator
  } 
 
  /** 
   * Writes Image Descriptor 
   * @throws IOException IOException
   */ 
  protected void writeImageDesc() throws IOException {
    out.write(0x2c); // image separator
    writeShort(0); // image position x,y = 0,0
    writeShort(0); 
    writeShort(width); // image size
    writeShort(height); 
    // packed fields
    if (firstFrame) {
      // no LCT - GCT is used for first (or only) frame
      out.write(0); 
    } else {
      // specify normal LCT
      out.write(0x80 | // 1 local color table 1=yes
          0 | // 2 interlace - 0=no
          0 | // 3 sorted - 0=no
          0 | // 4-5 reserved
          palSize); // 6-8 size of color table
    } 
  } 
 
  /** 
   * Writes Logical Screen Descriptor 
   * @throws IOException IOException
   */ 
  protected void writeLSD() throws IOException {
    // logical screen size
    writeShort(width); 
    writeShort(height); 
    // packed fields
    out.write((0x80 | // 1 : global color table flag = 1 (gct used)
        0x70 | // 2-4 : color resolution = 7
        0x00 | // 5 : gct sort flag = 0
        palSize)); // 6-8 : gct size
 
    out.write(0); // background color index
    out.write(0); // pixel aspect ratio - assume 1:1
  } 
 
  /**
   * Writes Netscape application extension to define repeat count. 
   * @throws IOException IOException
   */
  protected void writeNetscapeExt() throws IOException {
    out.write(0x21); // extension introducer
    out.write(0xff); // app extension label
    out.write(11); // block size
    writeString("NETSCAPE" + "2.0"); // app id + auth code
    out.write(3); // sub-block size
    out.write(1); // loop sub-block id
    writeShort(repeat); // loop count (extra iterations, 0=repeat forever)
    out.write(0); // block terminator
  } 
 
  /**
   * Writes color table 
   * @throws IOException IOException
   */
  protected void writePalette() throws IOException {
    out.write(colorTab, 0, colorTab.length); 
    int n = (3 * 256) - colorTab.length; 
    for (int i = 0; i < n; i++) {
      out.write(0); 
    } 
  } 
 
  /** 
   * Encodes and writes pixel data 
   * @throws IOException IOException
   */
  protected void writePixels() throws IOException {
    LZWEncoder encoder = new LZWEncoder(width, height, indexedPixels, colorDepth); 
    encoder.encode(out); 
  } 
 
  /** 
   * Write 16-bit value to output stream, LSB first
   * @param value value 
   * @throws IOException IOException
   */
  protected void writeShort(int value) throws IOException {
    out.write(value & 0xff); 
    out.write((value >> 8) & 0xff); 
  } 
 
  /** 
   * Writes string to output stream 
   * @param s s
   * @throws IOException IOException
   */ 
  protected void writeString(String s) throws IOException {
    for (int i = 0; i < s.length(); i++) {
      out.write((byte) s.charAt(i)); 
    } 
  } 
} 
 
// 
// Adapted from Jef Poskanzer's Java port by way of J. M. G. Elliott. 
// K Weiner 12/00 

class LZWEncoder {
 
  private static final int EOF = -1; 
 
  private int imgW, imgH; 
 
  private byte[] pixAry; 
 
  private int initCodeSize; 
 
  private int remaining; 
 
  private int curPixel; 
 
  // GIFCOMPR.C - GIF Image compression routines
  //
  // Lempel-Ziv compression based on 'compress'. GIF modifications by
  // David Rowley (mgardi@watdcsu.waterloo.edu)
 
  // General DEFINEs
 
  static final int BITS = 12; 
 
  static final int HSIZE = 5003; // 80% occupancy
 
  // GIF Image compression - modified 'compress'
  //
  // Based on: compress.c - File compression ala IEEE Computer, June 1984.
  //
  // By Authors: Spencer W. Thomas (decvax!harpo!utah-cs!utah-gr!thomas)
  // Jim McKie (decvax!mcvax!jim)
  // Steve Davies (decvax!vax135!petsd!peora!srd)
  // Ken Turkowski (decvax!decwrl!turtlevax!ken)
  // James A. Woods (decvax!ihnp4!ames!jaw)
  // Joe Orost (decvax!vax135!petsd!joe)
 
  int n_bits; // number of bits/code
 
  int maxbits = BITS; // user settable max # bits/code
 
  int maxcode; // maximum code, given n_bits
 
  int maxmaxcode = 1 << BITS; // should NEVER generate this code
 
  int[] htab = new int[HSIZE]; 
 
  int[] codetab = new int[HSIZE]; 
 
  int hsize = HSIZE; // for dynamic table sizing
 
  int free_ent = 0; // first unused entry
 
  // block compression parameters -- after all codes are used up,
  // and compression rate changes, start over.
  boolean clear_flg = false; 
 
  // Algorithm: use open addressing double hashing (no chaining) on the
  // prefix code / next character combination. We do a variant of Knuth's
  // algorithm D (vol. 3, sec. 6.4) along with G. Knott's relatively-prime
  // secondary probe. Here, the modular division first probe is gives way
  // to a faster exclusive-or manipulation. Also do block compression with
  // an adaptive reset, whereby the code table is cleared when the compression
  // ratio decreases, but after the table fills. The variable-length output
  // codes are re-sized at this point, and a special CLEAR code is generated
  // for the decompressor. Late addition: construct the table according to
  // file size for noticeable speed improvement on small files. Please direct
  // questions about this implementation to ames!jaw.
 
  int g_init_bits; 
 
  int ClearCode; 
 
  int EOFCode; 
 
  // output
  //
  // Output the given code.
  // Inputs:
  // code: A n_bits-bit integer. If == -1, then EOF. This assumes
  // that n_bits =< wordsize - 1.
  // Outputs:
  // Outputs code to the file.
  // Assumptions:
  // Chars are 8 bits long.
  // Algorithm:
  // Maintain a BITS character long buffer (so that 8 codes will
  // fit in it exactly). Use the VAX insv instruction to insert each
  // code in turn. When the buffer fills up empty it and start over.
 
  int cur_accum = 0; 
 
  int cur_bits = 0; 
 
  int masks[] = {0x0000, 0x0001, 0x0003, 0x0007, 0x000F, 0x001F, 0x003F, 0x007F, 0x00FF, 0x01FF,
      0x03FF, 0x07FF, 0x0FFF, 0x1FFF, 0x3FFF, 0x7FFF, 0xFFFF }; 
 
  // Number of characters so far in this 'packet'
  int a_count; 
 
  // Define the storage for the packet accumulator
  byte[] accum = new byte[256]; 


  LZWEncoder(int width, int height, byte[] pixels, int color_depth) {
    imgW = width; 
    imgH = height; 
    pixAry = pixels; 
    initCodeSize = Math.max(2, color_depth); 
  } 
 
  // Add a character to the end of the current packet, and if it is 254
  // characters, flush the packet to disk.
  void char_out(byte c, OutputStream outs) throws IOException {
    accum[a_count++] = c; 
    if (a_count >= 254) 
      flush_char(outs); 
  } 
 
  // Clear out the hash table
 
  // table clear for block compress
  void cl_block(OutputStream outs) throws IOException {
    cl_hash(hsize); 
    free_ent = ClearCode + 2; 
    clear_flg = true; 
 
    output(ClearCode, outs); 
  } 
 
  // reset code table
  void cl_hash(int hsize) {
    for (int i = 0; i < hsize; ++i) 
      htab[i] = -1; 
  } 
 
  void compress(int init_bits, OutputStream outs) throws IOException {
    int fcode; 
    int i /* = 0 */; 
    int c; 
    int ent; 
    int disp; 
    int hsize_reg; 
    int hshift; 
 
    // Set up the globals: g_init_bits - initial number of bits
    g_init_bits = init_bits; 
 
    // Set up the necessary values
    clear_flg = false; 
    n_bits = g_init_bits; 
    maxcode = MAXCODE(n_bits); 
 
    ClearCode = 1 << (init_bits - 1); 
    EOFCode = ClearCode + 1; 
    free_ent = ClearCode + 2; 
 
    a_count = 0; // clear packet
 
    ent = nextPixel(); 
 
    hshift = 0; 
    for (fcode = hsize; fcode < 65536; fcode *= 2) 
      ++hshift; 
    hshift = 8 - hshift; // set hash code range bound
 
    hsize_reg = hsize; 
    cl_hash(hsize_reg); // clear hash table
 
    output(ClearCode, outs); 
 
    outer_loop: while ((c = nextPixel()) != EOF) {
      fcode = (c << maxbits) + ent; 
      i = (c << hshift) ^ ent; // xor hashing
 
      if (htab[i] == fcode) {
        ent = codetab[i]; 
        continue; 
      } else if (htab[i] >= 0) // non-empty slot
      {
        disp = hsize_reg - i; // secondary hash (after G. Knott)
        if (i == 0) 
          disp = 1; 
        do {
          if ((i -= disp) < 0) 
            i += hsize_reg; 
 
          if (htab[i] == fcode) {
            ent = codetab[i]; 
            continue outer_loop; 
          } 
        } while (htab[i] >= 0); 
      } 
      output(ent, outs); 
      ent = c; 
      if (free_ent < maxmaxcode) {
        codetab[i] = free_ent++; // code -> hashtable
        htab[i] = fcode; 
      } else 
        cl_block(outs); 
    } 
    // Put out the final code.
    output(ent, outs); 
    output(EOFCode, outs); 
  } 


  void encode(OutputStream os) throws IOException {
    os.write(initCodeSize); // write "initial code size" byte
 
    remaining = imgW * imgH; // reset navigation variables
    curPixel = 0; 
 
    compress(initCodeSize + 1, os); // compress and write the pixel data
 
    os.write(0); // write block terminator
  } 
 
  // Flush the packet to disk, and reset the accumulator
  void flush_char(OutputStream outs) throws IOException {
    if (a_count > 0) {
      outs.write(a_count); 
      outs.write(accum, 0, a_count); 
      a_count = 0; 
    } 
  } 
 
  final int MAXCODE(int n_bits) {
    return (1 << n_bits) - 1; 
  } 
 
  // ----------------------------------------------------------------------------
  // Return the next pixel from the image
  // ----------------------------------------------------------------------------
  private int nextPixel() {
    if (remaining == 0) 
      return EOF; 
 
    --remaining; 
 
    byte pix = pixAry[curPixel++]; 
 
    return pix & 0xff; 
  } 
 
  void output(int code, OutputStream outs) throws IOException {
    cur_accum &= masks[cur_bits]; 
 
    if (cur_bits > 0) 
      cur_accum |= (code << cur_bits); 
    else 
      cur_accum = code; 
 
    cur_bits += n_bits; 
 
    while (cur_bits >= 8) {
      char_out((byte) (cur_accum & 0xff), outs); 
      cur_accum >>= 8; 
      cur_bits -= 8; 
    } 
 
    // If the next entry is going to be too big for the code size,
    // then increase it, if possible.
    if (free_ent > maxcode || clear_flg) {
      if (clear_flg) {
        maxcode = MAXCODE(n_bits = g_init_bits); 
        clear_flg = false; 
      } else {
        ++n_bits; 
        if (n_bits == maxbits) 
          maxcode = maxmaxcode; 
        else 
          maxcode = MAXCODE(n_bits); 
      } 
    } 
 
    if (code == EOFCode) {
      // At EOF, write the rest of the buffer.
      while (cur_bits > 0) {
        char_out((byte) (cur_accum & 0xff), outs); 
        cur_accum >>= 8; 
        cur_bits -= 8; 
      } 
 
      flush_char(outs); 
    } 
  } 
} 
 
/* 
 * NeuQuant Neural-Net Quantization Algorithm 
 * ------------------------------------------ 
 *  
 * Copyright (c) 1994 Anthony Dekker 
 *  
 * NEUQUANT Neural-Net quantization algorithm by Anthony Dekker, 1994. See 
 * "Kohonen neural networks for optimal colour quantization" in "Network: 
 * Computation in Neural Systems" Vol. 5 (1994) pp 351-367. for a discussion of 
 * the algorithm. 
 *  
 * Any party obtaining a copy of these files from the author, directly or 
 * indirectly, is granted, free of charge, a full and unrestricted irrevocable, 
 * world-wide, paid up, royalty-free, nonexclusive right and license to deal in 
 * this software and documentation files (the "Software"), including without 
 * limitation the rights to use, copy, modify, merge, publish, distribute, 
 * sublicense, and/or sell copies of the Software, and to permit persons who 
 * receive copies from any such party to do so, with the only requirement being 
 * that this copyright notice remain intact. 
 */

// Ported to Java 12/00 K Weiner 
class NeuQuant {
 
  protected static final int netsize = 256; /* number of colours used */ 
 
  /* four primes near 500 - assume no image has a length so large */ 
  /* that it is divisible by all four primes */ 
  protected static final int prime1 = 499; 
 
  protected static final int prime2 = 491; 
 
  protected static final int prime3 = 487; 
 
  protected static final int prime4 = 503; 
 
  protected static final int minpicturebytes = (3 * prime4); 
 
  /* minimum size for input image */ 
 
  /* 
   * Program Skeleton ---------------- [select samplefac in range 1..30] [read 
   * image from input file] pic = (unsigned char*) malloc(3*width*height); 
   * initnet(pic,3*width*height,samplefac); learn(); unbiasnet(); [write output 
   * image header, using writecolourmap(f)] inxbuild(); write output image using 
   * inxsearch(b,g,r) 
   */ 
 
  /* 
   * Network Definitions ------------------- 
   */ 
 
  protected static final int maxnetpos = (netsize - 1); 
 
  protected static final int netbiasshift = 4; /* bias for colour values */ 
 
  protected static final int ncycles = 100; /* no. of learning cycles */ 
 
  /* defs for freq and bias */ 
  protected static final int intbiasshift = 16; /* bias for fractions */ 
 
  protected static final int intbias = (((int) 1) << intbiasshift); 
 
  protected static final int gammashift = 10; /* gamma = 1024 */ 
 
  protected static final int gamma = (((int) 1) << gammashift); 
 
  protected static final int betashift = 10; 
 
  protected static final int beta = (intbias >> betashift); /* beta = 1/1024 */ 
 
  protected static final int betagamma = (intbias << (gammashift - betashift)); 
 
  /* defs for decreasing radius factor */ 
  protected static final int initrad = (netsize >> 3); /* 
                                                         * for 256 cols, radius 
                                                         * starts 
                                                         */ 
 
  protected static final int radiusbiasshift = 6; /* at 32.0 biased by 6 bits */ 
 
  protected static final int radiusbias = (((int) 1) << radiusbiasshift); 
 
  protected static final int initradius = (initrad * radiusbias); /* 
                                                                   * and 
                                                                   * decreases 
                                                                   * by a 
                                                                   */ 
 
  protected static final int radiusdec = 30; /* factor of 1/30 each cycle */ 
 
  /* defs for decreasing alpha factor */ 
  protected static final int alphabiasshift = 10; /* alpha starts at 1.0 */ 
 
  protected static final int initalpha = (((int) 1) << alphabiasshift); 
 
  protected int alphadec; /* biased by 10 bits */ 
 
  /* radbias and alpharadbias used for radpower calculation */ 
  protected static final int radbiasshift = 8; 
 
  protected static final int radbias = (((int) 1) << radbiasshift); 
 
  protected static final int alpharadbshift = (alphabiasshift + radbiasshift); 
 
  protected static final int alpharadbias = (((int) 1) << alpharadbshift); 
 
  /* 
   * Types and Global Variables -------------------------- 
   */ 
 
  protected byte[] thepicture; /* the input image itself */ 
 
  protected int lengthcount; /* lengthcount = H*W*3 */ 
 
  protected int samplefac; /* sampling factor 1..30 */ 
 
  // typedef int pixel[4]; /* BGRc */
  protected int[][] network; /* the network itself - [netsize][4] */ 
 
  protected int[] netindex = new int[256]; 
 
  /* for network lookup - really 256 */ 
 
  protected int[] bias = new int[netsize]; 
 
  /* bias and freq arrays for learning */ 
  protected int[] freq = new int[netsize]; 
 
  protected int[] radpower = new int[initrad]; 
 
  /* radpower for precomputation */ 
 
  /* 
   * Initialise network in range (0,0,0) to (255,255,255) and set parameters 
   * ----------------------------------------------------------------------- 
   */ 
  public NeuQuant(byte[] thepic, int len, int sample) {
 
    int i; 
    int[] p; 
 
    thepicture = thepic; 
    lengthcount = len; 
    samplefac = sample; 
 
    network = new int[netsize][]; 
    for (i = 0; i < netsize; i++) {
      network[i] = new int[4]; 
      p = network[i]; 
      p[0] = p[1] = p[2] = (i << (netbiasshift + 8)) / netsize; 
      freq[i] = intbias / netsize; /* 1/netsize */ 
      bias[i] = 0; 
    } 
  } 
 
  public byte[] colorMap() {
    byte[] map = new byte[3 * netsize]; 
    int[] index = new int[netsize]; 
    for (int i = 0; i < netsize; i++) 
      index[network[i][3]] = i; 
    int k = 0; 
    for (int i = 0; i < netsize; i++) {
      int j = index[i]; 
      map[k++] = (byte) (network[j][0]); 
      map[k++] = (byte) (network[j][1]); 
      map[k++] = (byte) (network[j][2]); 
    } 
    return map; 
  } 
 
  /* 
   * Insertion sort of network and building of netindex[0..255] (to do after 
   * unbias) 
   * ------------------------------------------------------------------------------- 
   */ 
  public void inxbuild() {
 
    int i, j, smallpos, smallval; 
    int[] p; 
    int[] q; 
    int previouscol, startpos; 
 
    previouscol = 0; 
    startpos = 0; 
    for (i = 0; i < netsize; i++) {
      p = network[i]; 
      smallpos = i; 
      smallval = p[1]; /* index on g */ 
      /* find smallest in i..netsize-1 */ 
      for (j = i + 1; j < netsize; j++) {
        q = network[j]; 
        if (q[1] < smallval) {/* index on g */
          smallpos = j; 
          smallval = q[1]; /* index on g */ 
        } 
      } 
      q = network[smallpos]; 
      /* swap p (i) and q (smallpos) entries */ 
      if (i != smallpos) {
        j = q[0]; 
        q[0] = p[0]; 
        p[0] = j; 
        j = q[1]; 
        q[1] = p[1]; 
        p[1] = j; 
        j = q[2]; 
        q[2] = p[2]; 
        p[2] = j; 
        j = q[3]; 
        q[3] = p[3]; 
        p[3] = j; 
      } 
      /* smallval entry is now in position i */ 
      if (smallval != previouscol) {
        netindex[previouscol] = (startpos + i) >> 1; 
        for (j = previouscol + 1; j < smallval; j++) 
          netindex[j] = i; 
        previouscol = smallval; 
        startpos = i; 
      } 
    } 
    netindex[previouscol] = (startpos + maxnetpos) >> 1; 
    for (j = previouscol + 1; j < 256; j++) 
      netindex[j] = maxnetpos; /* really 256 */ 
  } 
 
  /* 
   * Main Learning Loop ------------------ 
   */ 
  public void learn() {
 
    int i, j, b, g, r; 
    int radius, rad, alpha, step, delta, samplepixels; 
    byte[] p; 
    int pix, lim; 
 
    if (lengthcount < minpicturebytes) 
      samplefac = 1; 
    alphadec = 30 + ((samplefac - 1) / 3); 
    p = thepicture; 
    pix = 0; 
    lim = lengthcount; 
    samplepixels = lengthcount / (3 * samplefac); 
    delta = samplepixels / ncycles; 
    alpha = initalpha; 
    radius = initradius; 
 
    rad = radius >> radiusbiasshift; 
    if (rad <= 1) 
      rad = 0; 
    for (i = 0; i < rad; i++) 
      radpower[i] = alpha * (((rad * rad - i * i) * radbias) / (rad * rad)); 
 
    // fprintf(stderr,"beginning 1D learning: initial radius=%d\n", rad);
 
    if (lengthcount < minpicturebytes) 
      step = 3; 
    else if ((lengthcount % prime1) != 0) 
      step = 3 * prime1; 
    else {
      if ((lengthcount % prime2) != 0) 
        step = 3 * prime2; 
      else {
        if ((lengthcount % prime3) != 0) 
          step = 3 * prime3; 
        else 
          step = 3 * prime4; 
      } 
    } 
 
    i = 0; 
    while (i < samplepixels) {
      b = (p[pix + 0] & 0xff) << netbiasshift; 
      g = (p[pix + 1] & 0xff) << netbiasshift; 
      r = (p[pix + 2] & 0xff) << netbiasshift; 
      j = contest(b, g, r); 
 
      altersingle(alpha, j, b, g, r); 
      if (rad != 0) 
        alterneigh(rad, j, b, g, r); /* alter neighbours */ 
 
      pix += step; 
      if (pix >= lim) 
        pix -= lengthcount; 
 
      i++; 
      if (delta == 0) 
        delta = 1; 
      if (i % delta == 0) {
        alpha -= alpha / alphadec; 
        radius -= radius / radiusdec; 
        rad = radius >> radiusbiasshift; 
        if (rad <= 1) 
          rad = 0; 
        for (j = 0; j < rad; j++) 
          radpower[j] = alpha * (((rad * rad - j * j) * radbias) / (rad * rad)); 
      } 
    } 
    // fprintf(stderr,"finished 1D learning: final alpha=%f
    // !\n",((float)alpha)/initalpha);
  } 
 
  /* 
   * Search for BGR values 0..255 (after net is unbiased) and return colour 
   * index 
   * ---------------------------------------------------------------------------- 
   */ 
  public int map(int b, int g, int r) {
 
    int i, j, dist, a, bestd; 
    int[] p; 
    int best; 
 
    bestd = 1000; /* biggest possible dist is 256*3 */ 
    best = -1; 
    i = netindex[g]; /* index on g */ 
    j = i - 1; /* start at netindex[g] and work outwards */ 
 
    while ((i < netsize) || (j >= 0)) {
      if (i < netsize) {
        p = network[i]; 
        dist = p[1] - g; /* inx key */ 
        if (dist >= bestd) 
          i = netsize; /* stop iter */ 
        else {
          i++; 
          if (dist < 0) 
            dist = -dist; 
          a = p[0] - b; 
          if (a < 0) 
            a = -a; 
          dist += a; 
          if (dist < bestd) {
            a = p[2] - r; 
            if (a < 0) 
              a = -a; 
            dist += a; 
            if (dist < bestd) {
              bestd = dist; 
              best = p[3]; 
            } 
          } 
        } 
      } 
      if (j >= 0) {
        p = network[j]; 
        dist = g - p[1]; /* inx key - reverse dif */ 
        if (dist >= bestd) 
          j = -1; /* stop iter */ 
        else {
          j--; 
          if (dist < 0) 
            dist = -dist; 
          a = p[0] - b; 
          if (a < 0) 
            a = -a; 
          dist += a; 
          if (dist < bestd) {
            a = p[2] - r; 
            if (a < 0) 
              a = -a; 
            dist += a; 
            if (dist < bestd) {
              bestd = dist; 
              best = p[3]; 
            } 
          } 
        } 
      } 
    } 
    return (best); 
  } 
 
  public byte[] process() {
    learn(); 
    unbiasnet(); 
    inxbuild(); 
    return colorMap(); 
  } 
 
  /* 
   * Unbias network to give byte values 0..255 and record position i to prepare 
   * for sort 
   * ----------------------------------------------------------------------------------- 
   */ 
  public void unbiasnet() {
    for (int i = 0; i < netsize; i++) {
      network[i][0] >>= netbiasshift; 
      network[i][1] >>= netbiasshift; 
      network[i][2] >>= netbiasshift; 
      network[i][3] = i; /* record colour no */ 
    } 
  } 
 
  /* 
   * Move adjacent neurons by precomputed alpha*(1-((i-j)^2/[r]^2)) in 
   * radpower[|i-j|] 
   * --------------------------------------------------------------------------------- 
   */ 
  protected void alterneigh(int rad, int i, int b, int g, int r) {
 
    int j, k, lo, hi, a, m; 
    int[] p; 
 
    lo = i - rad; 
    if (lo < -1) 
      lo = -1; 
    hi = i + rad; 
    if (hi > netsize) 
      hi = netsize; 
 
    j = i + 1; 
    k = i - 1; 
    m = 1; 
    while ((j < hi) || (k > lo)) {
      a = radpower[m++]; 
      if (j < hi) {
        p = network[j++]; 
        try {
          p[0] -= (a * (p[0] - b)) / alpharadbias; 
          p[1] -= (a * (p[1] - g)) / alpharadbias; 
          p[2] -= (a * (p[2] - r)) / alpharadbias; 
        } catch (Exception e) {
        } // prevents 1.3 miscompilation
      } 
      if (k > lo) {
        p = network[k--]; 
        try {
          p[0] -= (a * (p[0] - b)) / alpharadbias; 
          p[1] -= (a * (p[1] - g)) / alpharadbias; 
          p[2] -= (a * (p[2] - r)) / alpharadbias; 
        } catch (Exception e) {
        } 
      } 
    } 
  } 
 
  /* 
   * Move neuron i towards biased (b,g,r) by factor alpha 
   * ---------------------------------------------------- 
   */ 
  protected void altersingle(int alpha, int i, int b, int g, int r) {
 
    /* alter hit neuron */ 
    int[] n = network[i]; 
    n[0] -= (alpha * (n[0] - b)) / initalpha; 
    n[1] -= (alpha * (n[1] - g)) / initalpha; 
    n[2] -= (alpha * (n[2] - r)) / initalpha; 
  } 
 
  /* 
   * Search for biased BGR values ---------------------------- 
   */ 
  protected int contest(int b, int g, int r) {
 
    /* finds closest neuron (min dist) and updates freq */ 
    /* finds best neuron (min dist-bias) and returns position */ 
    /* for frequently chosen neurons, freq[i] is high and bias[i] is negative */ 
    /* bias[i] = gamma*((1/netsize)-freq[i]) */ 
 
    int i, dist, a, biasdist, betafreq; 
    int bestpos, bestbiaspos, bestd, bestbiasd; 
    int[] n; 
 
    bestd = ~(((int) 1) << 31); 
    bestbiasd = bestd; 
    bestpos = -1; 
    bestbiaspos = bestpos; 
 
    for (i = 0; i < netsize; i++) {
      n = network[i]; 
      dist = n[0] - b; 
      if (dist < 0) 
        dist = -dist; 
      a = n[1] - g; 
      if (a < 0) 
        a = -a; 
      dist += a; 
      a = n[2] - r; 
      if (a < 0) 
        a = -a; 
      dist += a; 
      if (dist < bestd) {
        bestd = dist; 
        bestpos = i; 
      } 
      biasdist = dist - ((bias[i]) >> (intbiasshift - netbiasshift)); 
      if (biasdist < bestbiasd) {
        bestbiasd = biasdist; 
        bestbiaspos = i; 
      } 
      betafreq = (freq[i] >> betashift); 
      freq[i] -= betafreq; 
      bias[i] += (betafreq << gammashift); 
    } 
    freq[bestpos] += beta; 
    bias[bestpos] -= betagamma; 
    return (bestbiaspos); 
  } 
} 
